Three-dimensional (3D) depth capture systems extend conventional photography to a third dimension. While 2D images obtained from a conventional camera indicate color and brightness at each (x, y) pixel, 3D point clouds obtained from a 3D depth sensor indicate distance (z) to an object surface at each (x, y) pixel. Thus, a 3D sensor provides measurements of the third spatial dimension, z.
3D systems obtain depth information directly rather than relying on perspective, relative size, occlusion, texture, parallax and other cues to sense depth. Direct (x, y, z) data is particularly useful for computer interpretation of image data. Measured 3D coordinates of an object may be sent to a 3D printer to create a copy of the object, for example. Measured 3D coordinates of a human face may improve the accuracy of computer facial recognition algorithms and reduce errors due to changes in lighting.
Many techniques exist for 3D depth capture, but two of the most successful so far are time of flight and structured light approaches. Time of flight is based on measuring the round trip time for light to travel from a 3D depth capture system to an object and back. The farther away the object is, the longer the round trip time. Structured light is based on projecting a light pattern onto an object and observing the pattern from a vantage point separated from the projector. For example a pattern of parallel stripes projected onto a face appears distorted when viewed from a position away from the projector.
Current 3D depth capture systems are not small enough to be integrated into mobile electronic devices such as cell phones and tablet computers. Some systems have been packaged into centimeter scale enclosures that can be strapped onto tablets. For 3D depth capture to become a viable addition to mobile devices' sensor suites, however, miniaturization to the millimeter scale is needed.